Experimental details.
All hyperparameters are consistent with those of the baseline model across the ablation experiments.
In the models trained on the different data augmentation schemes, we vary only \(\alpha \) , i.e., the parameter defining \( Beta(\alpha ,\alpha )\) , from which the \(\lambda \)  parameter controlling the convex combination between data point pairs is sampled. Appropriately, we compare all methods varying \(\alpha \)  according to previous works [1]}, [2]}.
Across all models trained with NFM, we control the level of noise injections by fixing the additive noise level to \(\sigma _{add}=0.4\)  and multiplicative noise to \(\sigma _{mult}=0.2\) . To demonstrate the significant improvements on robustness upon the introduction of these small input perturbations, we compare against an ablation model (`*') that was injected with higher noise levels (i.e., \(\sigma _{add}=1.0\) , \(\sigma _{mult}=0.5\) ).
See SM (Section REF ) for further details and comparisons against NFM models trained on various other levels of noise injections.
